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Jingwen Zhang

Publications and source records attributed to Jingwen Zhang.

At least 19 recordsLinked to original sources

The $γ$ Cephei System: Updated Orbits, Dynamical Architecture, and Limits on Additional Companions

The $γ$ Cephei system hosts one of the first exoplanets discovered and is orbited by one of the closest known stellar companions to a planet-hosting star. Here, we derive updated orbital fits for $γ$ Cep AB, the stellar binary, and Ab, the planet, by combining literature data with \textit{Hipparcos-Gaia} astrometry, new radial velocities (RVs), and adaptive optics imaging. We acquired 328 RVs of $γ$ Cep A with Keck/HIRES, AFP/Levy, McDonald/Tull, and Whipple/TRES, and eight adaptive optics imaging epochs with Keck/NIRC2, including the earliest spatially resolved image of $γ$ Cep B in 2003. These observations extend the precision RV baseline of $γ$ Cep to 45 years and the direct imaging baseline to 23 years, improving inferred orbital parameter precisions by a factor of 2--10 compared to previous work. For $γ$ Cep B, we derive a semi-major axis of $a_B=20.07 \pm 0.06$ AU, a mass of $M_B=415 \pm 2$ $M_{Jup}$ ($0.396 \pm 0.002$ $M_{\odot}$), an eccentricity of $e_B=0.422 \pm 0.002$, and an inclination of $i_B=119.8^{\circ}\pm0.1^{\circ}$. For $γ$ Cep Ab, we find a separation of $a_{Ab}=1.978 \pm 0.007$ AU, a minimum mass of $M_{Ab} \sin i = 1.62 \pm 0.04$ $M_{Jup}$, and an eccentricity of $e_{Ab}=0.07 \pm0.03$. Using the RV residuals and dynamical constraints, we rule out additional Jovians between 2.5--20 AU, and companions more massive than Neptune for $a<1$ AU, both at $>90\%$ confidence. The absence of additional giant planets over a broad range of orbital separations is consistent with a dynamically sculpted system in which the close stellar companion limited the formation or long-term survival of other distant companions.

astro-ph.EP

Dynamical Mass Constraints on Transition Disk Perturbers with the G23H Catalog

We present dynamical mass constraints on perturbers in 11 transition disk systems using a novel combination of calibrated Hipparcos and Gaia absolute astrometry data. Out of the sample of 11, we find support for companions in four systems, with significant detections in two. These systems are: HD 142527, where we clearly detect the known low-mass stellar companion HD 142527 B and MWC 758, where we detect a likely sub-stellar companion. We also find moderate evidence of companions to AB Aur and UX Tau A. For the seven systems with non-detections, we find no evidence for companions more massive than $\sim$12 $M_{\mathrm{Jup}}$ with a semi-major axis greater than 3 au for both HD 100546 and HD 100453, nor for companions more massive than $\sim$3 $M_{\mathrm{Jup}}$ with a semi-major axis greater than 2 au for TW Hya. We also find no evidence for stellar mass companions with semi-major axes between $\sim$4 and $\sim$25 au for HD 34282, HD 97048, CQ Tau and RY Lup. In addition to our fiducial model, we perform cross validation between astrometry sources. By comparing results across models, we find tentative evidence of a short timescale excess astrometric noise that may impact some protoplanetary disk systems. We conclude with predictions for the prospects of making dynamical mass constraints on protoplanets in protoplanetary disk systems with Gaia data release 4 using detailed simulations of Gaia DR4 data of PDS 70 and WISPIT 2.

astro-ph.EP

The Roman Coronagraph Community Participation Program: corgisim - a simulation suite for the Nancy Grace Roman Space Telescope Coronagraph Instrument

NASA's Roman Space Telescope will feature a pathfinder Coronagraph Instrument to demonstrate advanced high-contrast imaging from space, paving the way for future missions like the Habitable Worlds Observatory. The Coronagraph Instrument could obtain imaging, polarimetry and spectroscopy of Jupiter analogs in reflected visible light for the first time. We present the development of an open-source simulation package ``corgisim'' as part of the Roman Coronagraph Community Participate Program. Built on established optical propagation libraries including PROPER and CGISim, corgisim provides a user-friendly, publicly available Python framework for end-to-end simulations of the Coronagraph Instrument observations. The package produces high-fidelity, format-compliant data for pre-launch calibration, pipeline testing, and community applications such as target selection and observation planning. We will give an overview of corgisim's infrastructure, functionalities, and current implementation across planned imaging, polarimetry, and spectroscopy modes, including the ability to simulate host stars, injected companions, and extended disks. We will also highlight suitable applications of corgisim and provide guidance on how users can access and employ the software.

astro-ph.IM

The Roman Coronagraph Community Participation Program: early calibration plan and pilot observation of a companion

Roman is set to launch in weeks! The Coronagraph Instrument - technology pathfinder for future direct imaging missions - is ready to fly too. According to predictions, laboratory tests and high fidelity simulations, it will open a new contrast regime enabling the imaging of mature, giant planets in visible reflected light. The Community Participation Program is responsible for preparing a comprehensive observing program with associated data processing software and calibrations. We give a brief update about the on-going "baseline" calibration plan for the first months. Additionally, we describe a pilot program aiming for the stellar companion HD 29992 B at moderate ~1e-5 to ~1e-6 Band 1 (575 nm) contrast, to be carried out as soon as the instrument is operational. The idea is to generate a canonical data set with a self luminous companion that is easily recoverable. This functional checkout will be precious to best prepare our community, exercise our calibration plan and suite of tools.

astro-ph.IM

The Roman Coronagraph Community Participation Program: data reduction pipeline design and implementation

The Roman Space Telescope Coronagraph Instrument will demonstrate a series of technologies and techniques to enable the direct detection of reflected-light planets with space-based observatories. To characterize and validate the performance of the Coronagraph Instrument, the Community Participation Program is developing corgidrp, an open-source Python-based data reduction pipeline. The pipeline can process data from the required and best-effort observing modes and their associated calibration sequences into calibrated science-ready data products. We present the software design and implementation of corgidrp and the motivation behind specific design decisions. We describe the software architecture, data flow, processing steps, automation tools, testing framework, and development philosophy. We also outline future development plans in preparation for on-sky data.

astro-ph.IM

The Roman Coronagraph Community Participation Program: pre-launch reference star list and impact of reference star properties on post-processing performance

The upcoming Roman Coronagraph will be the first high-contrast instrument in space capable of high-order wavefront sensing and control technologies, a critical technology demonstration for the proposed Habitable Worlds Observatory (HWO) that aims to directly image and characterize habitable exoEarths. The nominal Roman Coronagraph observing plan involves alternating observations of a science target and a bright, nearby reference star for both wavefront calibration and reference differential imaging post-processing. Reference star criteria for the most demanding coronagraph mode are restrictive, limiting the sample to only 40 candidates for which thorough observational vetting is needed to assess their suitability. Reference star properties such as resolved diameters, presence of circumstellar dust, and close point sources may also have more subtle impacts on post-processing efficacy that may inhibit final contrast performance. In this work, we describe the current progress of the CoronaGraph Instrument Reference stars for Exoplanets (CorGI-REx) observing campaign, a 300+-hour observing campaign that utilizes instruments from around the world to vet reference stars for high-order wavefront control suitability. We will present the pre-launch list of reference star candidates being utilized for the Roman Coronagraph Observation Phase constructed from a thorough analysis of high contrast and interferometric observations. We will also present the results of simulations investigating the impact of reference star resolved diameters and companions on post-processing performance. We conclude by discussing the importance of reference star selection for scheduling observations and optimizing contrast performance for the Roman Coronagraph along with implications for HWO coronagraph operations.

astro-ph.IM

The Roman Coronagraph Community Participation Program: Observation planning and data reduction for polarimetric mode

Reflected-light polarimetry of exoplanets constrains and resolves degeneracies in atmospheric properties, while polarized light observations of debris disks enable the characterization of dust-grain properties. The best-effort polarimetric mode of the Roman Coronagraph Instrument will be able to perform multi-wavelength observations of planetary systems using both the Hybrid Lyot Coronagraph (HLC) and the Shaped Pupil Coronagraph (SPC). This paper presents an overview of observation planning, simulations, and data reduction procedures for the polarimetric mode of the Roman Coronagraph. As an initial test of simulation and data reduction, a dataset of polarimetric observing sequences for the debris disk HD 172555 in HLC mode was generated using corgisim with estimated observation parameters, and data reduction was performed using corgidrp, incorporating all relevant noise factors and calibration products. Currently, mock calibration products are used in corgidrp; these will be replaced with simulated calibration products in future updates

astro-ph.IM

Gaia Exoplanet Orbits, Demographics, and Evolution Survey (GEODES): Characteristics of Three Long-Period Companions Accelerating their Host Stars

The upcoming release of $Gaia$ DR4 will yield thousands of giant planet candidates, eventually enabling studies of giant planet eccentricities, masses, and occurrence rates across a broad range of stellar host masses, metallicities, and ages. However, some of these planet candidates are expected to be false positives, and even genuine detections will require additional observations to precisely determine their orbits and masses. We present here the first results of the $Gaia$ Exoplanet Orbits, Demographics, and Evolution Survey (GEODES), an observational campaign to identify the most promising planet candidate hosts for pre-DR4 vetting and post-DR4 validation and characterization. In this paper we showcase three systems from our broader sample exhibiting both tangential and radial accelerations, each representing a distinct outcome of our survey strategy. We combine $Hipparcos$, $Hipparcos$-$Gaia$, $Gaia$ DR2, and $Gaia$ DR3 absolute astrometry with adaptive optics (AO) imaging and precision RVs to constrain companion masses and orbits. HIP 18512, a nearby (15.3 pc) K4V dwarf, hosts a low-mass stellar companion at 10.87" $\pm$ 0.07" (166 AU) which produces significant RV and astrometric accelerations on its host star. The RV trend and astrometric acceleration of the nearby (24.2 pc) K4V star HIP 45839, together with an AO imaging non-detection, constrain the companion to $a$ = 17.9^{+4.8}_{-2.7} AU ($P$ = 70--127 years) and $M$ = 45.2^{+10.5}_{-12.7} $M_{Jup}$. In the case of HIP 81991 (43.8 pc, G5V), the astrometric and RV data indicate that the companion has a separation of 6.4^{+0.6}_{-0.3} AU ($P$ = 14.4--17.7 years) and a mass of 9.5^{+5.4}_{-2.2} $M_{Jup}$, and is more likely a planet (65%) than a brown dwarf (35%).

astro-ph.EP

Text Distance from Nested and Hierarchical Repetitions: A Compression-Based Perspective

We present a new method for structural sequence analysis grounded in Algorithmic Information Theory (AIT). At its core is the Ladderpath approach, which extracts nested and hierarchical relationships among repeated substructures in linguistic sequences -- an instantiation of AIT's principle of describing data through minimal generative programs. These structures are then used to define three distance measures: a normalized compression distance (NCD), and two alternative distances derived directly from the Ladderpath representation. Integrated with a $k$-nearest neighbor classifier, these distances achieve strong and consistent performance across in-distribution, out-of-distribution (OOD), and few-shot text classification tasks. In particular, all three methods outperform both gzip-based NCD and BERT under OOD and low-resource settings. These results demonstrate that the structured representations captured by Ladderpath preserve intrinsic properties of sequences and provide a lightweight, interpretable, and training-free alternative for text modeling. This work highlights the potential of AIT-based approaches for structural and domain-agnostic sequence understanding.

cs.CL

Hydrogen airglow from an escaping ultrahot Jupiter atmosphere

Intense high-energy irradiation of close-in gaseous exoplanets drives the rapid escape of their atmospheres, fundamentally shaping planetary demographics. While atmospheric loss is routinely observed via transit absorption in atomic hydrogen, helium, and metal ions, the underlying physical properties, specifically the thermal structure, outflow dynamics, and mass-loss rate, remain poorly constrained due to inherent degeneracies in the transmission geometry. Here we report the first detection of atomic hydrogen emission from the escaping atmosphere of a gas giant. Using high-resolution spectroscopy of the ultrahot Jupiter KELT-9 b, we detect a hydrogen Balmer line (Hα 6564.6 Å) emission signature originating from the planetary dayside. The emission line profile features a distinctive double-peaked shape with 0.1-0.15% peak amplitudes at +/-30 km/s and central self-absorption. This profile breaks transmission degeneracies, providing direct observational constraints on the vertical thermal structure, excited-state hydrogen populations, and wind dynamics in the upper atmosphere of KELT-9 b. Initial modeling reveals a vigorous outflow with a mass-loss rate above 10^{13} g/s, among the highest measured to date for gaseous exoplanets. Our results establish hydrogen airglow emission as a powerful diagnostic of atmospheric escape, opening a new observational window into the evolution of worlds in extreme radiation environments.

astro-ph.EP

DLawBench: Evaluating LLMs Through Multi-Turn Legal Consultation

Lawyer-client consultation is a critical starting point for legal services. Effective legal assistance hinges on eliciting sufficient and truthful information from clients in order to devise strategies that best protect their interests. This task requires Large Language Models (LLMs) not only to perform robust legal reasoning, but also to strategically elicit material facts through multi-turn interactions and effectively guide clients with diverse personalities. Yet existing legal benchmarks overlook this interactive capability. To fill this gap, we introduce DLawBench, a diagnostic benchmark for real-world legal consultation. Drawing on realistic client behavior, we characterize lawyer-client interactions into four types: Cooperative, Dependent, Withdrawn, and Adversarial. Using dialogues grounded in real cases, DLawBench evaluates whether LLMs can effectively conduct legal consultation under realistic conditions. DLawBench comprises 461 cases from Chinese and U.S. law, 5,532 paired fact entries, 3,411 inquiry rubrics, and 3,348 issue-resolution rubrics, and evaluates 26 representative LLMs. Systematic experiments show substantial headroom: the best-performing model, GPT-5.5, achieves only 0.562 on consultation-grounded legal reasoning. More importantly, DLawBench exposes both sycophancy in legal consultation and a paradox: models perform worse when clients need guidance most.

cs.CL

mmAlert: A Simultaneous Device Localization and Target Tracking System via Cooperative Passive Sensing

In this paper, a cooperative passive sensing system in millimeter-wave (mmWave) band for simultaneous device localization and target tracking, namely mmAlert, is proposed. Specifically, in uplink communication with at least two transmitters, the receiver receives the line-of-sight (LoS) signals and the scattered signals off a moving target, respectively. Based on the received signals of the sensing time intervals, when a passive target moves along one or multiple unknown trajectories, mmAlert could measure the angles-of-arrival (AoAs) and bistatic Doppler frequencies of the echoes from the sensing target, and then jointly estimate the locations of the transmitters and the trajectories of the target. Specifically, the transmitters' locations and the moving target's trajectories can be searched by minimizing the weighted mean squared error of the AoA and Doppler measurements. The optimal solution of the minimization problem is prohibitive due to the large number of variables. Hence, a low-complexity algorithm based on the alternating optimization is proposed, where the extended Kalman filter (EKF) is introduced to quickly shape the trajectories. The mmAlert is implemented in a 60GHz communication testbed. The experiment shows with the received signal spanning a single trajectory, the average localization error of the transmitters and average trajectory reconstruction error are 0.76 m and 0.29 m, respectively. The average errors are suppressed to 0.07 m and 0.2 m respectively, if the received signal spanning 50 trajectories is used. This justifies the benefit of trajectory diversity in localization and tracking.

cs.NI

TCP-MCP: Landscape-Guided Co-Evolution of Prompts and Communication Topologies for Multi-Agent Systems

Effective multi-agent systems cannot be designed by selecting prompts or communication graphs in isolation. Agent behavior depends on the information an agent receives, while the usefulness of a communication edge depends on how the receiving agent interprets and uses that information. We propose \textbf{TCP-MCP} (Topology-Coupled Prompting for Multi-Agent Collaborative Problem-Solving), a co-evolution framework that searches agent prompts and communication topologies as a unified genome. TCP-MCP uses an initialization-time landscape probe to calibrate early search behavior, and then relies on Pareto-front diagnostics to adapt exploration under three objectives: task performance, token cost, and structural complexity. Using the same DeepSeek-V3.2 backbone across all methods, TCP-MCP achieves 82.66\%, 89.96\%, and 96.61\% accuracy on MMLU-Pro, MMLU, and GSM8K, respectively. Across the three benchmarks, it consistently outperforms automated graph-generation baselines and achieves competitive accuracy relative to debate-style systems, while using up to 5.69$\times$ fewer tokens than those systems at the reported operating points. These results show that jointly evolving prompts and communication structure provides a practical route to cost-aware and task-adaptive multi-agent system design in controlled evaluations.

cs.AI

The Labyrinth and the Thread: Rethinking Regularizations in Sequential Knowledge Editing for Large Language Models

Sequential editing of structured knowledge in large language models allows targeted factual updates without retraining, yet existing methods often rely on complex regularization or constraint mechanisms whose necessity remains unclear. In this work, we systematically investigate the mechanisms underlying effective and stable sequential editing. Specifically, we first analyze the empirical success of AlphaEdit and establish, via a rigorous optimization analysis, the formal equivalence between one-time and sequential editing. Building on this insight, we generalize the equivalence to a broader class of editing objectives, demonstrating that stability emerges naturally from properly accounting for accumulated editing constraints, rather than from specialized regularization or null-space operations. We empirically confirm that many commonly used regularization strategies are unnecessary for reliable sequential updates. Furthermore, we extend our framework to handle conflicting edits, ensuring robust and consistent behavior under contradictory updates. Ultimately, our work provides Ariadne's thread through the labyrinth of sequential editing, charting a path toward simpler, more interpretable, and dependable knowledge updates. Our code is available at https://github.com/Wangzzzzzzzz/OTE-SE-Alignment.

cs.CL

Closing the Motivation Gap: Incentives Enhance Visual Misinformation Discernment and Verification

Cheapfakes, or real images presented misleadingly or in unrelated contexts, are an increasingly prominent form of visual misinformation. While media literacy interventions can enhance individuals' ability to detect such content, motivational barriers often hinder the adoption of image verification. This study examines whether incorporating different mechanisms and types of incentives into a digital media literacy intervention improves visual misinformation discernment and image verification behavior, both immediately and over time. We conducted a pre-registered two-wave between-subjects online experiment (N = 1,421) on a professionally designed social media platform. The study used a 2 (Incentive Type: symbolic vs. monetary) x 2 (Incentive Mechanism: task- vs. result-based) factorial design with additional control groups. Results show that task-based incentives, particularly monetary ones, were most effective at initiating image verification behaviors, namely reverse image search, and boosting short-term discernment, whereas result-based incentives were more effective in sustaining discernment accuracy. These findings suggest that both the mechanism and the type of incentives play a critical role in shaping the short- and long-term effectiveness of media literacy interventions, highlighting the value of multi-phased incentive strategies for combating visual misinformation in digital environments.

cs.HC

An Outer Giant Planet or Brown Dwarf in the 51 Pegasi System?

51 Pegasi harbors the first confirmed extrasolar planet orbiting a Sun-like star. Decades of continued radial velocity (RV) observations have since uncovered signatures of an additional distant companion in the system from a shallow radial acceleration. We present new constraints on the mass and separation of a potential outer companion based on a synthesis of RVs, absolute astrometry, and new high-contrast imaging. Our analysis combines 31 years of new and previously published RV measurements from the OHP/ELODIE, Lick/Hamilton, Keck/HIRES, and APF/Levy spectrographs; a $\sim$25-year baseline of absolute astrometry from Hipparcos and Gaia; and deep imaging from Keck/NIRC2 and HST/WFPC2. We find evidence for curvature in the RVs, which when combined with non-detections from imaging and astrometry point to a super-Jupiter at $\simeq$15--100 AU or brown dwarf companion at $\approx$20--170 AU. However, the inferred radial acceleration of the host star is driven primarily by the Lick/Hamilton dataset and its slope is consistent with long-term instrument drift, calling into question the nature of the long-period signal. If an outer companion is present, it could explain the origin of the inner hot Jupiter if 51 Peg b arrived at its current location through high-eccentricity migration. On the other hand, if the signal is spurious, the exceptional baseline rules out Jovian planets within $\sim$10 AU and most brown dwarfs within several tens of AU, implying that the system is devoid of massive companions. Continued RV and astrometric monitoring together with high-contrast imaging can be used to distinguish these scenarios.

astro-ph.EP

A Computational Model of Message Sensation Value in Short Video Multimodal Features that Predicts Sensory and Behavioral Engagement

The contemporary media landscape is characterized by sensational short videos. While prior research examines the effects of individual multimodal features, the collective impact of multimodal features on viewer engagement with short videos remains unknown. Grounded in the theoretical framework of Message Sensation Value (MSV), this study develops and tests a computational model of MSV with multimodal feature analysis and human evaluation of 1,200 short videos. This model that predicts sensory and behavioral engagement was further validated across two unseen datasets from three short video platforms (combined N = 14,492). While MSV is positively associated with sensory engagement, it shows an inverted U-shaped relationship with behavioral engagement: Higher MSV elicits stronger sensory stimulation, but moderate MSV optimizes behavioral engagement. This research advances the theoretical understanding of short video engagement and introduces a robust computational tool for short video research.

cs.CV

V2E: Validating Smart Contract Vulnerabilities through Profit-driven Exploit Generation and Execution

Smart contracts are a critical component of blockchain systems. Due to the large amount of digital assets carried by smart contracts, their security is of critical importance. Although numerous tools have been developed for detecting smart contract vulnerability, their effectiveness remains limited, particularly due to the high false positives included in the reported results. Therefore, developers and auditors are often overwhelmed with manually verifying the reported issues. A fundamental reason behind this is that while a reported vulnerability satisfies specific vulnerable patterns, it may not actually be exploitable, either because the vulnerable code cannot be triggered or it does not result in any financial loss. In this paper, we propose V2E, a new framework for validating whether a reported vulnerability is truly exploitable. The core idea of V2E is to automatically generate executable Proof-of-Concept Exploit (PoC for short), and then assess if the vulnerability could be triggered and incur any real damage (i.e., causing financial loss) by the PoC. While LLMs have shown proficiency in PoC generation, achieving our task is by no means trivial. In detail, it is difficult for LLM to: (1) generate and update PoC to trigger a specific vulnerability, (2) evaluate the PoC's effectiveness to validate exploitable vulnerability. To this end, V2E automates the whole process through a novel combination of PoC generation, validation, and refinement: (1) Firstly, V2E generates targeted PoCs by analyzing potential vulnerability paths. (2) Then, V2E verifies the validity of PoCs through triggerability and profitability analysis. (3) In addition, V2E iteratively refines the generated PoC based on PoC execution feedback, therefore, increasing the chance to confirm the vulnerability. Evaluation on 264 manually labeled contracts shows that V2E outperforms the baseline approach.

cs.SE